bias_iteration_report: Build a bias-iteration report
In mfrmr: Estimation and Diagnostics for Many-Facet Measurement Models

bias_iteration_report

R Documentation

Build a bias-iteration report

Description

Build a bias-iteration report

Usage

bias_iteration_report(
  x,
  diagnostics = NULL,
  facet_a = NULL,
  facet_b = NULL,
  interaction_facets = NULL,
  max_abs = 10,
  omit_extreme = TRUE,
  max_iter = 4,
  tol = 0.001,
  top_n = 10
)

Arguments

`x`	Output from `estimate_bias()` or `fit_mfrm()`.
`diagnostics`	Optional output from `diagnose_mfrm()` (used when `x` is fit).
`facet_a`	First facet name (required when `x` is fit and `interaction_facets` is not supplied).
`facet_b`	Second facet name (required when `x` is fit and `interaction_facets` is not supplied).
`interaction_facets`	Character vector of two or more facets.
`max_abs`	Bound for absolute bias size when estimating from fit.
`omit_extreme`	Omit extreme-only elements when estimating from fit.
`max_iter`	Iteration cap for bias estimation when `x` is fit.
`tol`	Convergence tolerance for bias estimation when `x` is fit.
`top_n`	Maximum number of iteration rows to keep in preview-oriented summaries. The full iteration table is always returned.

Details

This report focuses on the recalibration path used by estimate_bias(). It provides a package-native counterpart to legacy iteration printouts by exposing the iteration table, convergence summary, and orientation audit in one bundle.

Value

A named list with:

table: iteration history
summary: one-row convergence summary
orientation_audit: interaction-facet sign audit
settings: resolved reporting options

Examples

toy <- load_mfrmr_data("example_bias")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
diag <- diagnose_mfrm(fit, residual_pca = "none")
out <- bias_iteration_report(fit, diagnostics = diag, facet_a = "Rater", facet_b = "Criterion")
summary(out)

mfrmr documentation built on March 31, 2026, 1:06 a.m.